Challenge
A Tier-1 automotive supplier was producing machined metal parts at a rate of 2 parts per second.
Their cloud-based vision system introduced 500ms+ latency, forcing production slowdowns.
Additionally, missed micro-defects (less than 0.5mm scratches) were leading to costly warranty claims.
Solution
- Edge Vision Hardware: Industrial global shutter camera integrated with an NVIDIA Jetson-based edge gateway.
- AI Detection Model: Custom YOLO-based model trained on real and GAN-generated synthetic defect datasets.
- Model Optimization: Quantized to FP16 and accelerated using TensorRT for high-performance GPU inference.
- Real-Time Pipeline: Local inference system delivering pass/fail results in under 20 milliseconds.
Outcome
- Ultra-Low Latency: Less than 20ms inference time (100x faster than cloud systems).
- High Accuracy: 99.7% defect detection accuracy compared to 85% manual inspection.
- Offline Reliability: Fully operational without internet dependency, eliminating downtime risks.
- Scalable Deployment: Successfully implemented across 5 production lines running 2 shifts daily.
Upgrade Your Manufacturing with AI
Deploy real-time edge AI solutions to eliminate defects, improve quality, and maximize production efficiency without relying on the cloud.
